THE 13 COMPETING TRIBES IN ARTIFICIAL INTELLIGENCE

One of the biggest confusions about “Artificial Intelligence” is that it is a very vague term. That’s because Artificial Intelligence or AI is a term that was coined back in 1955 with extreme hubris.

AI is over half a century old and carries too much baggage. For a very long time, AI was dominated by Symbolists, those who championed rule-based systems that had “Zero Learning”. In the 1980’s a new kind of AI began to emerge termed Machine Learning. Finally, we had at least “Simple Learning”. The big disruption, however, occurred this decade when we stumbled upon “Deep Learning”.

Of course, this is a grossly oversimplified history of AI. There are actually many different approaches or tribes in AI. Pedro Domingo’s in his book, the Master Algorithm, talks about five different “tribes” all vying for the “master algorithm”. Anyone that plans on doing AI should understand that there are differences in the approaches of the different tribes of AI.

AI is not a homogenous field, but rather a field in constant tribal warfare. Here’s an overview: